Sentimental Analysis on Cosmetics using Machine Learning

Abstract

Customer reviews of products are collected by Unified Computing System (UCS). It is a data-based computer server that is set up for evaluating hardware, programme management, and visualisation support. We employ Machine Learning algorithms to learn, evaluate, and identify customer information and data for the product based on previous customer feedback. We employ the Support Vector Machine (SVM), which is critical in dividing textual and hyper textual content into given groups. The SVM approach is useful for image classification, text reorganization, and handwriting character reorganization. We discovered that ML outperforms the other methods based on the results. When opposed to the other methods, the HRS (Human Resource System) that is proposed has a higher MAPE value of 96 percent and accuracy of nearly 98 percent. The proposed HRS has a mean absolute error of approximately 0.6, indicating that the system's efficiency is excellent.